A fast hybrid roundness evaluation algorithm based on computational geometry and particle swarm optimization for profiles with massive points

Bai, Xuelong; Wang, Wei; li, Wenhao; Liu, Zhaowu; Yu, Shuo; Bai, Yu; Chen, Guoxue

doi:10.1016/j.measurement.2023.113798

Search citation statements

Order By: Relevance

Paper Sections

Select...

Citation Types

Supporting

Mentioning

Contrasting

Year Published

2024

Publication Types

Select...

Book1

Article1

Relationship

Self Cite0

Independent2

Authors

Journals

Cited by 2 publications

References 49 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

Virtual Device for Assessing the Geometric Parameters’ Reliability Control for Mechanical Products Depending on the Tool Accuracy

Voichyshen,

Patsera,

Derbaba

et al. 2024

Lecture Notes in Mechanical Engineering

View full text Add to dashboard Cite

Virtual Device for Assessing the Geometric Parameters’ Reliability Control for Mechanical Products Depending on the Tool Accuracy

Voichyshen,

Patsera,

Derbaba

et al. 2024

Lecture Notes in Mechanical Engineering

View full text Add to dashboard Cite

Assessment of Femoral Head Sphericity Using Coordinate Data through Modified Differential Evolution Approach

Mian,

Almutairi,

Aboudaif

2024

Mathematics

View full text Add to dashboard Cite

Coordinate measuring machines (CMMs) are utilized to acquire coordinate data from manufactured surfaces for inspection reasons. These data are employed to gauge the geometric form errors associated with the surface. An optimization procedure of fitting a substitute surface to the measured points is applied to assess the form error. Since the traditional least-squares approach is susceptible to overestimation, it leads to unreasonable rejections. This paper implements a modified differential evolution (DE) algorithm to estimate the minimum zone femoral head sphericity. In this algorithm, opposition-based learning is considered for population initialization, and an adaptive scheme is enacted for scaling factor and crossover probability. The coefficients of the correlation factor and the uncertainty propagation are also measured so that the result’s uncertainty can be determined. Undoubtedly, the credibility and plausibility of inspection outcomes are strengthened by evaluating measurement uncertainty. Several data sets are used to corroborate the outcome of the DE algorithm. CMM validation shows that the modified DE algorithm can measure sphericity with high precision and consistency. This algorithm allows for an adequate initial solution and adaptability to address a wide range of industrial problems. It ensures a proper balance between exploitation and exploration capabilities. Thus, the suggested methodology, based on the computational results, is feasible for the online deployment of the sphericity evaluation. The adopted DE strategy is simple to use, has few controlling variables, and is computationally less expensive. It guarantees a robust solution and can be used to compute different form errors.

show abstract

A fast hybrid roundness evaluation algorithm based on computational geometry and particle swarm optimization for profiles with massive points

Cited by 2 publications

References 49 publications

Virtual Device for Assessing the Geometric Parameters’ Reliability Control for Mechanical Products Depending on the Tool Accuracy

Virtual Device for Assessing the Geometric Parameters’ Reliability Control for Mechanical Products Depending on the Tool Accuracy

Assessment of Femoral Head Sphericity Using Coordinate Data through Modified Differential Evolution Approach

Contact Info

Product

Resources

About